Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (8): 1881-1888.doi: 10.13229/j.cnki.jdxbgxb20210159

Previous Articles    

Text input based on two⁃handed keyboard in virtual environment

Gui-he QIN(),Jun-feng HUANG,Ming-hui SUN()   

  1. College of Computer Science and Technology,JiLin University,Changchun 130012,China
  • Received:2021-03-01 Online:2022-08-01 Published:2022-08-12
  • Contact: Ming-hui SUN E-mail:qingh@jlu.edu.cn;smh@jlu.edu.cn

Abstract:

Text input is the most common interaction behavior in viture reality(VR) environment, and the mainstream text input is currently realized by laser pointing. However, the existing methods have many drawbacks, such as low efficiency, large jitter, and easy false trigger, which cannot be used to frequently input text in VR environment. Therefore, a novel text input method for VR environment is proposed. First,First, partition the keyboard, use the handle to select the area where the characters are located, and use the word disambiguation algorithm to realize text input in units of words; secondly, perform cluster analysis on the user's click coordinates to do one-key multi-word processing; Finally, three keyboard layouts that conform to user habits are designed, and the optimal layout is determined The experimental results show that the typing speed of the optimal layout is 13.44 WPM(Words Per Minute) with an accuracy of 92.26%, which is a significant improvement compared with other input methods.

Key words: computer application technology, human-computer interaction, virtual reality, text input, word disambiguation

CLC Number: 

  • TP391.9

Fig.1

HTC Vive handle"

Fig.2

Clustering results of left and right hands"

Fig.3

Three layouts of QWERTY keyboard"

Fig.4

One-line one-key vocabulary tree structure"

Table 1

Number of words corresponding to the same sequence"

对应单词数一键布局/%两键布局/%三键布局/%
198.1996.8874.13
21.712.6613.06
30.100.445.09
4--3.82
5--2.04
6--0.80

Fig.5

Speed comparison of three layouts"

Fig.6

Comparison of three layout error rates"

Fig.7

Comparison of subjective experience of three layouts"

1 赵剑, 王柳, 史丽娟, 等. 面向言语康复的多模态人机交互系统[J]. 吉林大学学报: 工学版, 2020, 50(4): 1478-1486.
Zhao Jian, Wang Liu, Shi Li-juan, et al. Multimodal human-computer interaction system for speech rehabilitation[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(4): 1478-1486.
2 Bowman D A, Wingrave C A, Campbell J M, et al. Using pinch gloves(TM) for both natural and abstract interaction techniques in virtual environments[J/OL]. [2021-03-01].
3 Yu D, Fan K, Zhang H, et al. Pizzatext: text entry for virtual reality systems using dual thumbsticks[J]. IEEE Transactions on Visualization and Computer Graphics, 2018, 24(11): 2927-2935.
4 Kim Y R, Kim G J. Hovr-type: smartphone as a typing interface in vr using hovering[C]∥IEEE International Conference on Consumer Electronics(ICCE), Seoul, Republic of Korea, 2017: 200-203.
5 Lee Y, Kim G J. Vitty: virtual touch typing interface with added finger buttons[C]∥International Conference on Virtual, Augmented and Mixed Reality, Seoul, Republic of Korea, 2017: 111-119.
6 Cui W, Zheng J, Lewis B, et al. Hotstrokes: word-gesture shortcuts on a trackpad[C]∥Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland UK,2019: 1-13.
7 Bowman D A, Rhoton C J, Pinho M S. Text input techniques for immersive virtual environments: an empirical comparison[C]∥Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Baltimore, USA, 2002: 2154-2158.
8 Pick S, Puika A S, Kuhlen T W. Swifter: design and evaluation of a speech-based text input metaphor for immersive virtual environments[C]∥IEEE Symposium on 3D User Interfaces(3DUI), Greenville, USA, 2016: 109-112.
9 梁士利, 魏莹, 潘迪, 等. 基于语谱图行投影的特定人二字汉语词汇识别[J]. 吉林大学学报: 工学版, 2017, 47(1): 294-300.
Liang Shi-li, Wei Ying, Pan Di, et al. Recognition to specific two words Chinese vocabulary based on projection matrix of spectrogram[J]. Journal of Jilin University(Engineering and Technology Edition), 2017, 47(1): 294-300.
10 Wobbrock J O, Myers B A, Aung H H. Writing with a joystick: a comparison of date stamp, selection keyboard, and edgewrite[C]∥Proceedings of Graphics Interface, London, Canada, 2004: 1-8.
11 MacKenzie I S. KSPC (keystrokes per character) as a characteristic of text entry techniques[C]∥International Conference on Mobile Human-Computer Interaction, Berlin, Heidelberg, 2002: 195-210.
12 Venolia D, Neiberg F. T-Cube: a fast, self-disclosing pen-based alphabet[C]∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Pisa, Italy, 1994: 265-270.
13 Zhao S, Dragicevic P, Chignell M, et al. EarPod: eyes-free menu selection using touch input and reactive audio feedback[C]∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, California, USA, 2007: 1395-1404.
14 Benligiray B, Topal C, Akinlar C. SliceType: fast gaze typing with a merging keyboard[J]. Journal on Multimodal User Interfaces, 2019, 13(4): 321-334.
15 Mottelson A, Larsen C, Lyderik M, et al. Invisiboard: maximizing display and input space with a full screen text entry method for smartwatches[C]∥Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, Florence, Italy, 2016: 53-59.
16 Poirier F, Belatar M. Uniwatch: a soft keyboard for text entry on smartwatches using 3 keys watch user-interface and user evaluation[C]∥International Conference on Human-Computer Interaction, Toronto, Canada, 2016: 341-349.
17 Jiang H, Weng D. HiPad: text entry for head-mounted displays using circular touchpad[C]∥IEEE Conference on Virtual Reality and 3D User Interfaces(VR), Atlanta, United States, 2020: 692-703.
18 MacKenzie I S. Fitts' law as a research and design tool in human-computer interaction[J]. Human-computer Interaction, 1992, 7(1): 91-139.
19 Vertanen K, Kristensson P O. Complementing text entry evaluations with a composition task[J]. ACM Transactions on Computer-Human Interaction, 2014, 21(2): 2555691.
20 Levenshtein V I. Binary codes capable of correcting deletions, insertions, and reversals[J]. Soviet Physics Doklady, 1966, 10(8): 707-710.
[1] Tian BAI,Ming-wei XU,Si-ming LIU,Ji-an ZHANG,Zhe WANG. Dispute focus identification of pleading text based on deep neural network [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(8): 1872-1880.
[2] Fu-heng QU,Tian-yu DING,Yang LU,Yong YANG,Ya-ting HU. Fast image codeword search algorithm based on neighborhood similarity [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(8): 1865-1871.
[3] Zhen WANG,Meng GAI,Heng-shuo XU. Surface reconstruction algorithm of 3D scene image based on virtual reality technology [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(7): 1620-1625.
[4] Ming LIU,Yu-hang YANG,Song-lin ZOU,Zhi-cheng XIAO,Yong-gang ZHANG. Application of enhanced edge detection image algorithm in multi-book recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(4): 891-896.
[5] Shi-min FANG. Multiple source data selective integration algorithm based on frequent pattern tree [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(4): 885-890.
[6] Sheng-sheng WANG,Jing-yu CHEN,Yi-nan LU. COVID⁃19 chest CT image segmentation based on federated learning and blockchain [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 2164-2173.
[7] Hong-wei ZHAO,Zi-jian ZHANG,Jiao LI,Yuan ZHANG,Huang-shui HU,Xue-bai ZANG. Bi⁃direction segmented anti⁃collision algorithm based on query tree [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(5): 1830-1837.
[8] Jie CAO,Xue QU,Xiao-xu LI. Few⁃shot image classification method based on sliding feature vectors [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(5): 1785-1791.
[9] Chun-bo WANG,Xiao-qiang DI. Cloud storage integrity verification audit scheme based on label classification [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(4): 1364-1369.
[10] Rong QIAN,Ru ZHANG,Ke-jun ZHANG,Xin JIN,Shi-liang GE,Sheng JIANG. Capsule graph neural network based on global and local features fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 1048-1054.
[11] Qian-yi XU,Gui-he QIN,Ming-hui SUN,Cheng-xun MENG. Classification of drivers' head status based on improved ResNeSt [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 704-711.
[12] Yuan SONG,Dan-yuan ZHOU,Wen-chang SHI. Method to enhance security function of OpenStack Swift cloud storage system [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(1): 314-322.
[13] Xiang-jiu CHE,You-zheng DONG. Improved image recognition algorithm based on multi⁃scale information fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(5): 1747-1754.
[14] HU Guan-yu, QIAO Pei-li. High dimensional differential evolutionary algorithm based on cloud population for network security prediction [J]. 吉林大学学报(工学版), 2016, 46(2): 568-577.
[15] ZHAO Wei, QU Hui-yan. Fast collision detection algorithm based on Cloud Map-Reduce model [J]. 吉林大学学报(工学版), 2016, 46(2): 578-584.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!